Follow-Up Data Improve the Estimation of the Prevalence of Heavy Alcohol Consumption.

2018

Aims. We aim to adjust for potential non-participation bias in the prevalence of heavy alcohol consumption. Methods. Population survey data from Finnish health examination surveys conducted in 1987–2007 were linked to the administrative registers for mortality and morbidity follow-up until end of 2014. Utilising these data, available for both participants and non-participants, we model the association between heavy alcohol consumption and alcohol-related disease diagnoses. Results. Our results show that the estimated prevalence of heavy alcohol consumption is on average of 1.5 times higher for men and 1.8 times higher for women than what was obtained from participants only (complete case an…

Bayesian models for data missing not at random in health examination surveys

2018

In epidemiological surveys, data missing not at random (MNAR) due to survey nonresponse may potentially lead to a bias in the risk factor estimates. We propose an approach based on Bayesian data augmentation and survival modelling to reduce the nonresponse bias. The approach requires additional information based on follow-up data. We present a case study of smoking prevalence using FINRISK data collected between 1972 and 2007 with a follow-up to the end of 2012 and compare it to other commonly applied missing at random (MAR) imputation approaches. A simulation experiment is carried out to study the validity of the approaches. Our approach appears to reduce the nonresponse bias substantially…

Mark-recapture estimation of mortality and migration rates for sea trout (Salmo trutta) in the northern Baltic sea

2016

Knowledge of current fishing mortality rates is an important prerequisite for formulating management plans for the recovery of threatened stocks. We present a method for estimating migration and fishing mortality rates for anadromous fishes that combines tag return data from commercial and recreational fisheries with expert opinion in a Bayesian framework. By integrating diverse sources of information and allowing for missing data, this approach may be particularly applicable in data-limited situations.Wild populations of anadromous sea trout (Salmo trutta) in the northern Baltic Sea have undergone severe declines, with the loss of many populations. The contribution of fisheries to this dec…

Correction: Correcting for non-ignorable missingness in smoking trends

2017

Adjusting for selective non-participation with re-contact data in the FINRISK 2012 survey

2018

Aims: A common objective of epidemiological surveys is to provide population-level estimates of health indicators. Survey results tend to be biased under selective non-participation. One approach to bias reduction is to collect information about non-participants by contacting them again and asking them to fill in a questionnaire. This information is called re-contact data, and it allows to adjust the estimates for non-participation. Methods: We analyse data from the FINRISK 2012 survey, where re-contact data were collected. We assume that the respondents of the re-contact survey are similar to the remaining non-participants with respect to the health given their available background informa…

Correcting for non-ignorable missingness in smoking trends

2015

Data missing not at random (MNAR) is a major challenge in survey sampling. We propose an approach based on registry data to deal with non-ignorable missingness in health examination surveys. The approach relies on follow-up data available from administrative registers several years after the survey. For illustration we use data on smoking prevalence in Finnish National FINRISK study conducted in 1972-1997. The data consist of measured survey information including missingness indicators, register-based background information and register-based time-to-disease survival data. The parameters of missingness mechanism are estimable with these data although the original survey data are MNAR. The u…

Utilising mark-recapture data for Bayesian modelling of fish mortality

2013

In this work, the aim was to produce a realistic assessment of yearly mortality of Archipelago Sea pike perch during the period 1997-2012. The utilized data origins from the mark-recapture experiment carried out by the Finnish Game and Fisheries Research Institute (FGFRI). In this mark-recapture experiment, returnings of the marks were based on voluntary tag reporting by the fishermen gaining small monetary rewards. In this study design, the count of returned tags is affected by the size of the release cohort, efficiency of the fishing method used by a fisherman and the fisherman’s willingness to return the tag. In addition, each year a proportion of the tags become detached from fish, whic…

Itseopiskelumateriaalia: Kausaalimallintamisen perusteet tilastotieteessä

2016

Tämä moniste on tarkoitettu itseopiskelumateriaaliksi tilastotieteen maisterivaiheen opiskelijoille (tai vastaavat tiedot omaaville). Erityisesti todennäköisyyslaskennan ja yleistettyjen lineaaristen mallien tuntemus on tarpeen. Materiaalin tarkoituksena on selvittää lukijalle perusteet Judea Pearlin kehittämästä kausaalimallintamisesta ja -laskennasta. Materiaali perustuu Judea Pearlin kirjaan Causality [Pearl, 2009]. Lauseiden ja määritelmien kohdalla annetaan aina kirjan osio, josta nämä löytyvät. nonPeerReviewed